Keshav0308/multilingual-topic-classifier

1{2  "add_cross_attention": false,3  "architectures": [4    "XLMRobertaForSequenceClassification"5  ],6  "attention_probs_dropout_prob": 0.1,7  "bos_token_id": 0,8  "classifier_dropout": null,9  "dtype": "float32",10  "eos_token_id": 2,11  "hidden_act": "gelu",12  "hidden_dropout_prob": 0.1,13  "hidden_size": 768,14  "id2label": {15    "0": "geography",16    "1": "science/technology",17    "2": "entertainment",18    "3": "politics",19    "4": "health",20    "5": "travel",21    "6": "sports"22  },23  "initializer_range": 0.02,24  "intermediate_size": 3072,25  "is_decoder": false,26  "label2id": {27    "entertainment": 2,28    "geography": 0,29    "health": 4,30    "politics": 3,31    "science/technology": 1,32    "sports": 6,33    "travel": 534  },35  "layer_norm_eps": 1e-05,36  "max_position_embeddings": 514,37  "model_type": "xlm-roberta",38  "num_attention_heads": 12,39  "num_hidden_layers": 12,40  "output_past": true,41  "pad_token_id": 1,42  "position_embedding_type": "absolute",43  "problem_type": "single_label_classification",44  "tie_word_embeddings": true,45  "transformers_version": "5.0.0",46  "type_vocab_size": 1,47  "use_cache": false,48  "vocab_size": 25000249}50